An improved approximation algorithm for spanning star forest in dense graphs

2Citations
Citations of this article
4Readers
Mendeley users who have this article in their library.
Get full text

Abstract

A spanning subgraph of a given graph G is called a spanning star forest of G if it is a collection of node-disjoint trees of depth at most 1 (such trees are called stars). The size of a spanning star forest is the number of leaves in all its components. The goal of the spanning star forest problem [12] is to find the maximum-size spanning star forest of a given graph. In this paper, we study this problem in c-dense graphs, where for c ∈ (0,1), a graph of n vertices is called c-dense if it contains at least cn 2/2 edges [2]. We design a (α+(1-α)√c-ε)-approximation algorithm for spanning star forest in c-dense graphs for any ε>0, where α = 193/240 is the best known approximation ratio of the spanning star forest problem in general graphs [3]. Thus, our approximation ratio outperforms the best known bound for this problem when dealing with c-dense graphs. We also prove that for any c ∈ (0,1), there is a constant ε = ε(c) > 0 such that approximating spanning star forest in c-dense graphs within a factor of 1 - ε is NP-hard. We then demonstrate that for weighted versions (both node- and edge- weighted) of this problem, we cannot get any approximation algorithm with strictly better performance guarantee in c-dense graphs than that of the best possible approximation algorithm for general graphs. Finally, we give strong hardness-of-approximation results for a closely related problem, the minimum dominating set problem, in c-dense graphs. © 2010 Springer-Verlag.

Cite

CITATION STYLE

APA

He, J., & Liang, H. (2010). An improved approximation algorithm for spanning star forest in dense graphs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6509 LNCS, pp. 160–169). https://doi.org/10.1007/978-3-642-17461-2_13

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free